Initial commit: Clean DSS implementation

Migrated from design-system-swarm with fresh git history.
Old project history preserved in /home/overbits/apps/design-system-swarm

Core components:
- MCP Server (Python FastAPI with mcp 1.23.1)
- Claude Plugin (agents, commands, skills, strategies, hooks, core)
- DSS Backend (dss-mvp1 - token translation, Figma sync)
- Admin UI (Node.js/React)
- Server (Node.js/Express)
- Storybook integration (dss-mvp1/.storybook)

Self-contained configuration:
- All paths relative or use DSS_BASE_PATH=/home/overbits/dss
- PYTHONPATH configured for dss-mvp1 and dss-claude-plugin
- .env file with all configuration
- Claude plugin uses ${CLAUDE_PLUGIN_ROOT} for portability

Migration completed: $(date)
🤖 Clean migration with full functionality preserved

tools/config.py

@@ -0,0 +1,127 @@
+"""
+DSS Configuration Management
+
+Secure configuration loading with:
+- Environment variables (highest priority)
+- .env files
+- Default values
+
+Never logs or exposes sensitive values.
+"""
+
+import os
+from pathlib import Path
+from typing import Optional
+from dataclasses import dataclass
+
+# Try to load dotenv if available
+try:
+    from dotenv import load_dotenv
+    # Load from multiple possible locations (first found wins)
+    project_root = Path(__file__).parent.parent
+    env_locations = [
+        project_root / ".env",                    # Project root
+        project_root / "dss-mvp1" / ".env",       # dss-mvp1 subdirectory
+    ]
+    for env_path in env_locations:
+        if env_path.exists():
+            load_dotenv(env_path)
+            break
+except ImportError:
+    pass
+
+
+@dataclass
+class FigmaConfig:
+    """Figma API configuration."""
+    token: Optional[str] = None
+    cache_ttl: int = 300  # 5 minutes
+
+    @classmethod
+    def from_env(cls) -> "FigmaConfig":
+        return cls(
+            token=os.getenv("FIGMA_TOKEN"),
+            cache_ttl=int(os.getenv("FIGMA_CACHE_TTL", "300"))
+        )
+
+    @property
+    def is_configured(self) -> bool:
+        return bool(self.token)
+
+
+@dataclass
+class DatabaseConfig:
+    """Database configuration."""
+    path: str = ".dss/dss.db"
+
+    @classmethod
+    def from_env(cls) -> "DatabaseConfig":
+        return cls(
+            path=os.getenv("DATABASE_PATH", ".dss/dss.db")
+        )
+
+
+@dataclass
+class ServerConfig:
+    """Server configuration."""
+    port: int = 3456
+    host: str = "0.0.0.0"
+    env: str = "development"
+    log_level: str = "info"
+
+    @classmethod
+    def from_env(cls) -> "ServerConfig":
+        return cls(
+            port=int(os.getenv("PORT", "3456")),
+            host=os.getenv("HOST", "0.0.0.0"),
+            env=os.getenv("NODE_ENV", "development"),
+            log_level=os.getenv("LOG_LEVEL", "info")
+        )
+
+    @property
+    def is_production(self) -> bool:
+        return self.env == "production"
+
+
+@dataclass
+class Config:
+    """Main configuration container."""
+    figma: FigmaConfig
+    database: DatabaseConfig
+    server: ServerConfig
+
+    @classmethod
+    def load(cls) -> "Config":
+        """Load configuration from environment."""
+        return cls(
+            figma=FigmaConfig.from_env(),
+            database=DatabaseConfig.from_env(),
+            server=ServerConfig.from_env()
+        )
+
+    def summary(self) -> dict:
+        """Return config summary (no secrets)."""
+        return {
+            "figma": {
+                "configured": self.figma.is_configured,
+                "cache_ttl": self.figma.cache_ttl
+            },
+            "database": {
+                "path": self.database.path
+            },
+            "server": {
+                "port": self.server.port,
+                "env": self.server.env,
+                "log_level": self.server.log_level
+            }
+        }
+
+
+# Global config instance
+config = Config.load()
+
+
+if __name__ == "__main__":
+    import json
+    print("DSS Configuration:")
+    print(json.dumps(config.summary(), indent=2))